maha_dist {assertr} | R Documentation |

## Computes mahalanobis distance for each row of data frame

### Description

This function will return a vector, with the same length as the number of rows of the provided data frame, corresponding to the average mahalanobis distances of each row from the whole data set.

### Usage

```
maha_dist(data, keep.NA = TRUE, robust = FALSE, stringsAsFactors = FALSE)
```

### Arguments

`data` |
A data frame |

`keep.NA` |
Ensure that every row with missing data remains NA in the output? TRUE by default. |

`robust` |
Attempt to compute mahalanobis distance based on robust covariance matrix? FALSE by default |

`stringsAsFactors` |
Convert non-factor string columns into factors? FALSE by default |

### Details

This is useful for finding anomalous observations, row-wise.

It will convert any categorical variables in the data frame into numerics
as long as they are factors. For example, in order for a character
column to be used as a component in the distance calculations, it must
either be a factor, or converted to a factor by using the
`stringsAsFactors`

parameter.

### Value

A vector of observation-wise mahalanobis distances.

### See Also

### Examples

```
maha_dist(mtcars)
maha_dist(iris, robust=TRUE)
library(magrittr) # for piping operator
library(dplyr) # for "everything()" function
# using every column from mtcars, compute mahalanobis distance
# for each observation, and ensure that each distance is within 10
# median absolute deviations from the median
mtcars %>%
insist_rows(maha_dist, within_n_mads(10), everything())
## anything here will run
```

*assertr*version 3.0.1 Index]